A robot is a mechanical or virtual, artificial agent. It is usually an electro mechanical system, which, by its appearance or movements, conveys a sense that it has intent or agency of its own.

A typical robot will have several, though not necessarily all of the following properties:

• Is not 'natural' i.e. has been artificially created.

• Can sense its environment.

• Can manipulate things in its environment.

• Has some degree of intelligence or ability to make choices based on the environment or automatic control / pre-programmed sequence.

• Is programmable.

• Can move with one or more axes of rotation or translation.

• Can make dexterous coordinated movements.

• Appears to have intent or agency (reification, anthropomorphisation or Pathetic fallacy).

SELF HEALING OR SELF MODELLING ROBOTS

When people or animal get injured ,they compensate for minor injuries and keep limping along. But in the case of robots, even a slight injury can make them stumble and fall .Self healing robots have an ability to adapt to minor injuries and continue its job . A robot is able to indirectly infer its own morphology through self- directed exploration and then use the resulting self-models to synthesize new behaviors.If the robot's topology unexpectedly changes, the same process restructures it's internal self-models, leading to the generation of qualitatively different, compensatory behavior. In essence, the process enables the robot to continuously diagnose and recover from damage. Unlike other approaches to damage recovery, the concept introduced here does not presuppose built-in redundancy, dedicated sensor arrays, or contingency plans designed for anticipated failures. Instead, our approach is based on the concept of multiple competing internal models and generation of actions to maximize disagreement between predictions of these models.

Characterizing the Target System

The target system in this study is a quadrupedal, articulated robot with eight actuated degrees of freedom. The robot consists of a rectangular body and four legs attached to it with hinge joints on each of the four sides of the robot's body. Each leg in turn is composed of an upper and lower leg, attached together with a hinge joint. All eight hinge joints of the robot are actuated with Airtronics 94359 high torque servomotors. However, in the current study, the robot was simplified by assuming that the knee joints are frozen: all four legs are held straight when the robot is commanded to perform some action. The following table gives the overall dimensions of the robot's parts.

CONCLUSION

Although the possibility of autonomous self-modeling has been suggested, here it was demonstrated for the first time a physical system able to autonomously recover its own topology with little or no prior knowledge, as well as optimize the parameters of those resulting self-models after unexpected morphological change. These processes demonstrate both topological and parametric self-modeling. This suggests that future machines may be able to continually detect changes in their own morphology (e.g., after damage has occurred or when grasping a new tool) or the environment (when the robot enters an unknown or changed environment) and use the inferred models to generate compensatory behavior. Beyond robotics, the ability to actively generate and test hypotheses can lead to general nonlinear and topological system identification in other domains, such as computational systems, biological networks, damaged structures, and even automated science. Aside from practical value, the robot's abilities suggest a similarity to human thinking as the robot tries out various actions to figure out the shape of its world.